AI-based Network Function Virtualization Orchestration
Heegon Kim, Jae‐Hyoung Yoo, James Won‐Ki Hong · 2024
Network orchestration is pivotal in automating device, equipment, and service management within the network system. Currently, Network Function Virtualization (NFV) offers immense potential, but the challenge still lies in designing a capable orchestrator for dynamic networks. To address this challenge, we propose an AI-based NFV Orchestration Framework that leverages self-learning capabilities to detect dynamic network changes and make optimal decisions. This framework covers a range of essential functionalities, including NFV Orchestration, VNF Deployment, Service Function Chaining (SFC), Auto-Scaling, Migration, Anomaly Detection, Power Management, and Attack & Intrusion Detection. These functions collectively form a comprehensive ML-driven orchestration framework that offers adaptability, intelligence, and efficiency across the entire NFV environment. Our proposed structure aims for zero-touch automation, contributing to the efficient management of dynamic NFV network environments, and making it a compelling solution for the future of networking.